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相关概念视频

Wind Turbine Machine Models01:24

Wind Turbine Machine Models

627
In the growing field of wind energy, incorporating wind turbine models into transient stability analysis is essential. Induction and synchronous machines are the primary models used, with induction machines being prevalent due to their simplicity and reliability.
Induction machines interact through the rotating magnetic field generated by the stator and the rotor. The key parameter is slip, which is the difference between synchronous speed and rotor speed relative to synchronous speed. Slip is...
627
Transient and Steady-state Response01:24

Transient and Steady-state Response

607
In control systems, test signals are essential for evaluating performance under various conditions. The ramp function is effective for systems undergoing gradual changes, while the step function is suitable for assessing systems facing sudden disturbances. For systems subjected to shock inputs, the impulse function is the most appropriate test signal.
These test signals are integral in designing control systems to exhibit two key performance aspects: transient response and steady-state...
607
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

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A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
508
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

382
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
382
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

783
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
783
Design Example: Strain Gauge Bridge or Wheatstone Bridge01:15

Design Example: Strain Gauge Bridge or Wheatstone Bridge

1.1K
The utilization of strain gauges as transducers for converting mechanical strain into electrical signals is a common practice in various engineering applications. These strain gauges are frequently integrated into Wheatstone bridge circuits to accurately measure parameters such as force or pressure. Within this context, each element within the circuit exhibits a resistance that undergoes subtle variations when subjected to mechanical strain. The primary objective is to convert minuscule...
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相关实验视频

Updated: Feb 25, 2026

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
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Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

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一个新的桥梁风感应振动响应预测算法基于时间卷积网络.

Youlai Qu1, Xiangrong Bai1, Tianhao Zhu2

  • 1Power China Broadbridge Group Co. Ltd, Urumqi, Xinjiang, China.

PloS one
|February 23, 2026
PubMed
概括

使用时间卷积网络 (TCN) 的新算法准确地预测了桥梁在施工期间风引起的振动. 这种方法通过克服分析复杂的风力响应数据的挑战来提高安全性.

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科学领域:

  • 结构工程 结构工程
  • 计算力学 计算力学 计算力学
  • 数据科学数据科学数据科学

背景情况:

  • 高和长吊杆的桥梁在施工过程中容易受到风引起的振动,这会造成严重的安全风险.
  • 风振动反应的非线性和随机性质在施工阶段对准确的预测提出了挑战.

研究的目的:

  • 通过使用时卷积网络 (TCN) 在施工过程中对桥梁风引起的振动反应提出一种新的预测算法.
  • 评估基于TCN的模型与其他先进算法的预测准确度和概括能力.

主要方法:

  • 利用TCN内的因果卷积来识别风引起的振动加速数据中的映射关系.
  • 使用扩展卷积来捕捉风振动响应的多尺度特征.
  • 实施剩余连接以减轻网络中的梯度消失问题.

主要成果:

  • 基于TCN的模型与反复神经网络 (RNN),长期短期记忆 (LSTM) 和封闭单元网络 (GRU) 模型相比,显示出更高的预测准确度和概括能力.
  • 该算法有效地预测了多个方向的风振动加速,包括扭矩,垂直,横向和沿着桥梁.

结论:

  • 拟议的基于TCN的算法提供了一个强大的,准确的解决方案,用于预测桥梁在施工期间的风引起的振动反应.
  • 这一进步有助于改善桥梁工程项目的安全性和风险管理,特别是在强风环境中.